- Visibility18
- Citations1
- Sentiment82
- Site quality67
- AI readiness29
AI assistants name MarketAxess in 16.7% of answers, which is much more often than the typical company in the finance sector at 3.3%. Its overall score is 36 out of 100, ranking 730th of 2,047 companies. The MarketAxess website passes 2 of 14 technical checks for readiness for AI tools.
We asked 15 unbranded questions about the finance market: none named MarketAxess. AI assistants named it in 10 of 60 answers (16.7%). The typical finance company is named in 3.3% of answers. By how often it is named, MarketAxess ranks 34 of 205 in its sector.
Every dot is a company in the study. Hover one to see it; click to open its report.
This companySame sectorEvery other companyNever named
Five parts, each scored out of 100.
How often AI assistants name the company
How often AI uses the company's own website as a source
How positively AI describes the company
How well built the website's own pages are
How easily AI tools can read and use the website
Visibility is calculated from the answers on this page. How the score is built.
205 companies in this sector. The line on each bar is the typical company.
An answer that names the company
“What are the best electronic trading platforms for U.S. fixed income securities?”
For trading U.S. fixed income securities, several electronic trading platforms stand out, catering to different types of investors and their specific needs.
Top Platforms for Individual Investors:
Fidelity is frequently cited as the best overall for bond trading, offering a dedicated Fixed Income Dashboard and extensive inventory with over 100,000 new issue and secondary market offerings. They charge a transparent $1 mark-up or mark-down per bond for secondary trades and $0 for online U.S. Treasury trades.
Charles Schwab is highly regarded for its fixed-income education a …
The AI’s answer as we received it, shortened and not checked for accuracy.
How the mentions in these answers were split between this company and its rivals
Answers naming it, out of answers received
What this website publishes for an AI agent to read, use and buy from, on a scale of six levels.
- 0
- 1
- 2
- 3
- 4
- 5
Level 0: Not yet agent-ready. Agents struggle to find basic information about the site.
- 2 of robots.txt, Sitemap, Link headers
Show every check, for your technical teamHide the checks
- study: 92.0%robots.txtPassed
A valid robots.txt with crawl rules at the site root.
- study: 86.8%SitemapNot met
Serve an XML sitemap and reference it from robots.txt.
- study: 0.3%Link headersNot met
Send Link headers such as rel="api-catalog" or rel="describedby" on the homepage.
- study: 5.5%DNS for AI DiscoveryNot present
Advertise agent endpoints with SVCB records under _agents.
- study: 1.9%Markdown negotiationNot met
Return a markdown version when asked with Accept: text/markdown, for example at the CDN.
- study: 25.1%llms.txtNot met
Publish an llms.txt with a short summary and the key links.
- study: 93.4%AI bot rulesPartly met
Add explicit robots.txt groups for the main AI crawlers.
- study: 1.4%Content SignalsNot met
Add a Content-Signal line for search, ai-input and ai-train to robots.txt.
- study: 0.2%Web Bot AuthNot present
Only relevant if you run your own agents or crawlers: publish a signing key directory.
- study: 0.3%API CatalogNot met
List public APIs in a linkset at /.well-known/api-catalog.
- study: 11.8%OAuth discoveryNot met
Publish OpenID Connect or OAuth server metadata under /.well-known.
- study: 10.3%OAuth Protected ResourceNot met
Serve protected resource metadata at /.well-known/oauth-protected-resource.
- study: 0.0%auth.mdNot met
Publish an auth.md describing how agents sign in.
- study: 0.2%MCP Server CardNot met
Offer an MCP server and publish its server card under /.well-known.
- study: 0.1%A2A Agent CardNot met
Publish an agent card at /.well-known/agent-card.json.
- study: 0.2%Agent SkillsNot met
Publish a skills index with the main tasks agents can do.
- study: 33.7%WebMCPCould not check
Register key actions such as search or cart as WebMCP tools.
- study: 0.1%ARD manifestNot met
Publish an ai-catalog.json listing every agent interface.
Score 16 of 100 · 97% of checks could run · checked on October 5, 2026 · www.marketaxess.com · 2,047 companies scanned
2 of 14 passed. This list is for your technical team. The percentage is how many companies in the study pass each check.
These 14 checks ran during the audit and are what the AI readiness part of the overall score counts. The scan above ran later and is stricter on Link headers and Markdown, so a check can pass here and not there.
Show the 14 checksHide them
- Passedrobots.txt publishedstudy: 85.0%
- Not metXML sitemapstudy: 73.2%
- Not metHTTP Link headers (RFC 8288)study: 29.0%
- Not metMarkdown content negotiationstudy: 8.3%
- Not metllms.txt publishedstudy: 21.7%
- PassedToken budget (page weight)study: 95.2%
- Not metExplicit AI bot rulesstudy: 13.0%
- Not metAPI Catalog (.well-known/api-catalog)study: 0.2%
- Not metOAuth Authorization Server discoverystudy: 10.1%
- Not metOAuth Protected Resource discoverystudy: 9.3%
- Not metMCP Server Cardstudy: 0.0%
- Not metA2A Agent Cardstudy: 0.0%
- Not metWebMCP toolsstudy: 4.2%
- Not metAgent Skills declaredstudy: 0.0%
This website sets no rules for any AI crawler by name, like 84% of the websites whose rules we could read. Every AI crawler follows its general rules.
- GPTBotpartly
- ClaudeBotpartly
- Anthropic-AIpartly
- Google-Extendedpartly
- Applebot-Extendedpartly
- Meta-ExternalAgentpartly
- FacebookBotpartly
- Bytespiderpartly
- CCBotpartly
- Diffbotpartly
- Omgilibotpartly
- OAI-SearchBotpartly
- Claude-SearchBotpartly
- PerplexityBotpartly
- Applebotpartly
- Amazonbotpartly
- YouBotpartly
- ChatGPT-Userpartly
- Claude-Userpartly
- Perplexity-Userpartly
- DuckAssistBotpartly
- MistralAI-Userpartly
Read from the website’s own rules file (robots.txt). An asterisk marks a crawler the file names. The rest follow its general rules. “Partly” means only some pages are blocked.
How many times each website was listed as a source in these answers
In the study as US-listed.
- What are the differences between RFQ-based and order book trading platforms for bonds?
- What are some alternative workflow tools for fixed income traders besides electronic platforms?
- Are there non-electronic options for large institutional bond trades in the United States?
- What are effective ways to use real-time market depth analysis in credit trading?
- What are the best electronic trading platforms for U.S. fixed income securities?
- What are the typical pricing models for electronic fixed income trading platforms?
- Are electronic bond trading platforms worth it for improving workflow efficiency?
- How do all-to-all electronic fixed income platforms compare to single-dealer systems for large trades?
- How much does it cost for institutional investors to access advanced fixed income trading interfaces?
- What alternatives exist to all-to-all electronic platforms for trading U.S. bonds?
- How do you resolve connectivity issues with electronic fixed income trading platforms?
- Do real-time pricing tools in electronic trading platforms justify their subscription costs?
- Which digital solutions are popular for institutional credit trading in the United States?
- How can AI-powered insights enhance portfolio management for fixed income traders?
- What steps should you take if a bond order fails to execute on an electronic trading system?
Columns, left to right: OpenAI, Claude, Perplexity, Gemini. The AI assistants often disagree. Across the study, on 40% of the questions where a company is named, only one of the four names it.
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<a href="https://aeo-audit.rezolve.com/us/marketaxess.com"><img src="https://aeo-audit.rezolve.com/us/badges/marketaxess.com.svg" alt="Overall score 36 of 100, US AI Visibility Study 2026" width="280" height="64"></a>